Triple

T11549767
Position Surface form Disambiguated ID Type / Status
Subject Okusha Hohaisho E273859 entity
Predicate locatedIn P40 FINISHED
Object Kyoto City E10010 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kyoto City | Statement: [Okusha Hohaisho, locatedIn, Kyoto City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyoto City
Context triple: [Okusha Hohaisho, locatedIn, Kyoto City]
  • A. Kyoto chosen
    Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
  • B. Osaka
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • C. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • D. Fuji City
    Fuji City is an industrial city in Shizuoka Prefecture, Japan, known for its paper manufacturing industry and views of nearby Mount Fuji.
  • E. Osaka and Kyoto
    Osaka and Kyoto are two major cities in Japan’s Kansai region, renowned respectively for modern urban culture and historic temples, shrines, and traditional architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d886e615b08190a072924329a94a6a completed April 10, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69f62a7133d88190813a1e74ef310993 completed May 2, 2026, 4:46 p.m.
Created at: April 8, 2026, 9:37 p.m.